Estimation of population ratio in cluster sampling over successive sampling in the presence of non-response

Quality & Quantity - In this paper, we have discussed the problem of estimating the population ratio in cluster sampling over two occasion successive sampling in the presence of non-response....     

Modelling the antecedents of consumers' willingness to pay for eco-labelled food products

The purpose of this paper is to model the antecedents of consumers' willingness to pay for eco-labelled food products. This research utilizes the Theory of Planned Behaviour to model the impact of consumers' awareness of eco-labels, environmental concerns, beliefs in the environmental ability of eco-labels, and presence of children on their willingness to pay for eco-labelled food products. This study uses structural equational modelling and PROCESS macros, to test the moderated mediation model on a sample of 333 online responses. Findings suggest the impact of consumers' environmental concerns and eco-label awareness on their willingness to pay for eco-labelled food products is partially mediated by consumers' belief in the environmental ability of these eco-labels. The relationship is further moderated by the presence of children living in the household. This study establishes the value of consumers' beliefs in the environmental ability of eco-labels and implies that communication strategies need to be carefully refined to provide consumers with more information about eco-labels and to emphasize the environmental ability of eco-labels utilized within the food industry as this can have an impact on their willingness to pay for these products, especially for consumers, who have children in the same household.     

How can banks and finance companies incorporate value chain factors in their risk management strategy? The case of agro-food firms

A value chain framework for guiding the financial firms in their credit decisions is urgent, as the current COVID-19 pandemic has highlighted, but missing in the extant literature, particularly for those that lend to industries sensitive to value and supply chain bottlenecks. This study creates knowledge in value chain finance, a big untapped and un-researched market. It constructs, confirms, and validates a value chain framework for assessing risks in lending to Agro and Food Processing firms in which value chain risks are major business concerns globally. To pursue the objectives of the study, we use a novel methodology that integrates the Modified Delphi technique, exploratory factor analysis, confirmatory factor analysis, and discriminant analysis. Based on testing and analysis of primary data, including loan data, a framework comprising six factors is proposed for use in conjunction with existing risk assessment models of finance companies to improve the quality of their credit decisions, contributing to their performance sustainability.     

Benchmarking sustainable E-commerce enterprises based on evolving customer expectations amidst COVID-19 pandemic

The 2019 coronavirus disease (COVID-19) pandemic has seriously impacted the performance of all types of businesses. It has given a tremendous structural boost to e-commerce enterprises by forcing customers to online shopping over visiting physical stores. Moreover, customer expectations of the digital and operational capabilities of e-commerce firms are also increasing globally. Thus, it has become crucial for an e-commerce enterprise to reassess and realign its business practices to meet evolving customer needs and remain sustainable. This paper presents a comprehensive performance evaluation framework for e-commerce enterprises based on evolving customer expectations due to the COVID-19 pandemic. The framework comprises seven primary criteria, which are further divided into 25 sub-criteria, including two sustainability factors, namely, environmental sustainability and carbon emissions. The evaluation approach is then practically demonstrated by analyzing the case of three Indian e-commerce firms. The results are obtained using a multi-criteria decision-making (MCDM) method, namely, Fuzzy VIKOR, to capture the fuzziness of the inherent decision-making problem. Further, numerical analysis is conducted to evaluate and rank various e-commerce enterprises based on customer expectations and satisfaction benchmarks. The findings explain the most important criteria and sub-criteria for e-commerce businesses to ensure customer expectations along with their economic and environmental sustainability.     

Emotions and consumer behaviour: A review and research agenda

Consumers' emotions play a salient role in consumers' buying process, their consumption behaviours, and their engagement with product/service offerings, owing to which, it has gained much attention in recent years as an area of inquiry. However, literature in this field/subject is theoretically fragmented. Therefore, to enhance the conceptual understanding, this study synthesizes extant literature, using a hybrid review approach. Herein, we attempt to integrate bibliometric analysis, along with the theories, contexts, characteristics, and methodology framework, while consolidating and classifying the domain knowledge, trends, and progress/citation analysis using the bibliometric approach. In the process, we reviewed 384 conceptual and empirical articles, published during the period 1967–2021. The idea was to identify key theories, constructs, research contexts, and methods, based on which, we propose a few potential research areas. Based on our thorough analysis, these areas include (1) consumer co-creation, (2) consumer engagement, (3) service employee interactions, (4) consumer decision making, and (5) consumption experience.     

Digital innovation: An essence for Industry 4.0

The goal of this paper is to explain why digital innovation is so important in business organizations in order to survive in Industry 4.0. The study helps to understand the new era of Industry 4.0 and the importance of introducing digital innovation into organizations. A systematic review of the literature and studies on Industry 4.0 and digital innovation were synthesized to find answers to the research questions. To improve their manufacturing industry, organizations have implemented digital technologies such as augmented reality, robotic sensing, artificial intelligence, cloud computing, cyber physical systems, and remote sensing technologies. These technologies focused on automating logistics and supply chain systems, improving manufacturing system performance, and simplifying automated production systems. Because digital innovations save time and energy, employees can devote more time and energy to creative and innovative activities. Organizations should plan to implement digital technology in order to keep the environment healthy and sustainable while meeting the demands of customers, consumers, and the Industry 4.0 dimension.